Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

BACKGROUND: Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. METHODS: Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively. RESULTS: Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error. CONCLUSIONS: Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

Pinealitis accompanying equine recurrent uveitis.

There is no direct verification of pineal gland involvement in human uveitis. Specimens of pineal tissue are not available during active uveitis in human patients. Naturally occurring uveitis in horses gives us an opportunity to examine tissues during active ocular inflammation. We examined the pineal gland of a horse that was killed because it had become blind during an episode of uveitis. The clinical history and histopathology of the eyes were consistent with post-leptospiral equine recurrent uveitis. The pineal gland of this horse had significant inflammatory infiltration consisting mainly of lymphocytes with some eosinophils. This observation of pinealitis accompanying equine uveitis supports the animal models of experimental autoimmune uveoretinitis with associated pinealitis and suggests that the pineal gland may be involved in some human uveitides.

Pinealitis coincident with recurrent uveitis: immunohistochemical studies.

Although experimental models of autoimmune uveitis predict pinealitis coincident with uveitis, there is no direct evidence of pineal pathology accompanying a human uveitis. Horses with naturally occurring uveitis are a potential source of eye and pineal tissues that are not available from human patients with active uveitis. We have observed pinealitis in a mare with equine recurrent uveitis. By immunohistochemistry we demonstrated immunoglobulin and MHC Class II antigen on infiltrating and resident cells of eye and pineal gland. These results support the relevance of the animal models and suggest that pinealitis may be coincident with some human uveitides.

Immunochemical evaluation of S-antigen of rabbit pineal gland.

Purified S-antigen of photoreceptor cells induces experimental autoimmune uveoretinitis (EAU) and experimental autoimmune pinealitis (EAP) in laboratory animals. However, in rabbits, S-antigen induces only EAU without EAP. To evaluate this difference, the authors studied immunochemical reactivity of rabbit pineal gland with a panel of anti-S-antigen monoclonal antibodies (MAb). Rabbit pineal gland reacted with the MAbs by ELISA and immunoblot but not by immunohistochemistry. In contrast, rabbit retina like guinea pig retina, guinea pig pineal gland and bovine retina reacted with these MAbs by immunohistochemistry as well as by ELISA and immunoblot. Also, S-antigen purified from rabbit retina reacted as did bovine and guinea pig S-antigen. Therefore, S-antigen in situ in rabbit pineal gland is different from S-antigen of rabbit retina and different from S-antigen of pineal gland and retina of other species. Just as the MAbs did not react with S-antigen in rabbit pineal gland, it is possible that S-antigen activated lymphocytes may not recognize S-antigen in rabbit pineal gland and thereby not induce EAP.

Physical determinants of line pressures during apheresis.

Line pressure changes are inherent to apheresis procedures, although little work has been done to determine their physical basis. We developed a mathematical model in which fluid pressure within apheresis tubing is primarily dependent upon viscosity and hematocrit (HCT). Return line flow rates and pressures during plasma collections for peripheral blood stem cell (PBSC) harvest and during plasma exchange procedures using the COBE Spectra were recorded and used to model return line pressures. Pressure estimates were similar to measured values for both PBSC plasma collection (r2 = 0.70) and plasma exchange (r2 = 0.86). HCT and viscosity thus appear to be primary physical determinants that underlie these pressure changes.

Mathematical modeling and computer simulation of erythrocytapheresis for SCD.

BACKGROUND: Erythrocytapheresis is used to prevent acute chest syndrome and stroke in patients with sickle cell disease (SCD). However, such regimens are associated with significant risks, such as iron overload and potential exposure to transfusion-transmitted infectious diseases. Computer modeling of erythrocytapheresis procedures may help optimize treatments and minimize risks. STUDY DESIGN AND METHODS: Mathematical models based upon material balance equations and patient-specific statistical analyses were developed to estimate HbS levels immediately after erythrocytapheresis and immediately before the next treatment. The equations were incorporated into a software application that was used to model the effects of various treatment values on four patients treated with 90 erythrocytapheresis procedures. RESULTS: Immediate postprocedure HbS values were accurately estimated with correlations between measured and calculated values ranging from R(2) = 0.83 to 0.96. Estimates of HbS just before the next treatment correlated well in three patients (R(2) = 0.71 to 0.83) but poorly in one (R(2) = 0.28 to 0.46). Varying the treatment values by computer simulation led to a wide variation in the number of RBC units and the net RBC volume transfused. CONCLUSION: Computer modeling of erythrocytapheresis can be used to optimize chronic treatment regimens for SCD patients and potentially to minimize the risks of overtransfusion.